The present invention relates to signal processing, and more particularly to the measurement of signal levels and time delays at multiple signal sensors.
In many signal processing applications, it is desirable to determine the relative sensitivity of multiple signal sensors with respect to a particular signal source. For example, in the context of hands-free mobile telephony, dual microphones can be used in combination with beamforming methods to reduce the effects of background noise and echoes in an automobile. To do so, information regarding the relative sensitivities of the microphones with respect to different acoustic sources is used, for example, to form a spatial beam toward a particular user and/or to form a spatial notch against another user or a loudspeaker. Such an approach requires that dynamic information with respect to microphone sensitivity be quickly and accurately obtained.
FIG. 1 depicts a prior art system 100 for measuring the relative sensitivities of dual microphones with respect to different signal sources in the context of hands-free mobile telephony. As shown, the prior art system 100 includes a first microphone 115, a second microphone 125, an adaptive filter 135 and a summing device 140. An output y1(k) of the first microphone 115 is coupled to a positive input of the summing device 140, and an output ŷ2(k) of the second microphone 125 is coupled to an input of the adaptive filter 135. An output ŷ1(k) of the adaptive filter 135 is coupled to a negative input of the summing device 140, and an output e(k) of the summing device 140 is used as a feedback signal to the adaptive filter 135.
As shown, the first microphone 115 is positioned nearer a first source 110, and the second microphone 125 is positioned nearer a second source 120. For example, the first microphone 115 can be a hands-free microphone attached to a sun visor situated nearer a driver of an automobile, and the second microphone 125 can be a built-in microphone within a mobile unit attached nearer a passenger in the automobile. Although it is not shown in FIG. 1, those skilled in the art will appreciate that analog pre-processing and analog-to-digital conversion circuitry can be included at the output of each of the first and second microphones 115, 125 so that digital signals are processed by the adaptive filter 135 and the summing device 140. The output e(k) of the summing device 140 represents the difference between the output y1(k) of the first microphone 115 and the output ŷ1(k) of the adaptive filter 135 and is referred to herein as an error signal.
In operation, filter coefficients of the adaptive filter 135 are adjusted using a least-squares algorithm such that the error signal e(k) is minimized. In other words, the adaptive filter 135 is adjusted such that the output ŷ1(k) of the adaptive filter 135 is as close as possible to (i.e., is an estimator of) the output y1(k) of the first microphone 115. Thus, the adaptive filter 135 attempts to model the signal effects created by the physical separation of the microphones 115, 125. For example, when the passenger 120 is speaking, his or her voice will reach the first microphone 115 slightly later than it will reach the second microphone 125, and the corresponding speech signal level received at the first microphone 115 will be somewhat attenuated as compared to the level received at the second microphone 125. Thus, the adaptive filter 135 is adjusted to provide similar delay and attenuation effects.
As a result, the relative time delay and signal attenuation at the microphones with respect to each user can be calculated based on the coefficients of the adaptive filter 135 as described, for example, in Y. T. Chan, J. M. Riley and J. B. Plant, xe2x80x9cA parameter estimation approach to time delay estimation and signal detectionxe2x80x9d, IEEE Transactions on Acoustics, Speech and Signal Processing, vol. ASSP-28, February, 1980, which is incorporated herein in its entirety by reference. One disadvantage of the system of FIG. 1, however, is that its performance deteriorates significantly in the presence of background noise. As a result, the system of FIG. 1 is not useful in most practical applications, where significant background noise (e.g., road and traffic noise) is commonplace. Thus, there is a need for improved methods and apparatus for measuring relative signal levels and time delays at multiple sensors.
The present invention fulfills the above-described and other needs by providing a system in which a fixed filter and an adaptive filter are used in combination to provide accurate and robust estimates of signal levels and time delays for multiple sensors. In exemplary embodiments, the fixed filter includes at least one relatively narrow passband which is used to distinguish signal sources of interest from broad-band background noise. In the embodiments, the fixed filter is coupled to a reference sensor and the adaptive filter is coupled to a secondary sensor. An error signal derived from the outputs of the fixed filter and the adaptive filter is used to adjust filter coefficients of the adaptive filter according to a suitable least-squares algorithm. The coefficients of the fixed filter and the adaptive filter are used to compute estimates of the time delay and relative level between the two sensors. The estimates can then be used to make decisions regarding sensor selection and beamforming.
In exemplary embodiments, the functionality of the system is supplemented with an activity detector which indicates when no signal of interest is present. In the activity detector, accumulated energy in the adaptive filter is compared with an expected least value derived from the coefficients of the fixed filter. When the accumulated energy is smaller than the expected value, indicating that there is no signal of interest present (i.e., only background noise is present), the time delay and relative level estimates are set to appropriate values to ensure proper operation of the system even during periods where no signals of interest are present.
In additional embodiments, more than two signal sensors are employed. In such embodiments, one sensor is treated as a reference sensor and coupled to a fixed filter, while each of the additional sensors is coupled to an adaptive filter. For each additional sensor, an error signal derived from the outputs of the fixed filter and the corresponding adaptive filter is used to update the coefficients of the corresponding adaptive filter. Thus, robust estimates of the time delay and relative signal level between the reference sensor and each additional sensor can be computed, and sophisticated decisions can be made with respect sensor selection and beamforming.
Generally, the present invention provides a computationally simple yet accurate and robust method for estimating the time delays and relative signal levels at multiple sensors. The teachings of the invention are applicable in a wide variety of signal processing contexts. For example, in addition to the hands-free mobile telephony application described above, the invention may be used for other acoustic applications such as teleconferencing. Additionally, the present invention is applicable in radio communication applications where the signals of interest are radio-frequency transmissions (e.g., from mobile units and/or base stations in a cellular radio system) and the sensors are radio-frequency-sensitive antenna elements. These and other features and benefits of the present invention are explained hereinafter with reference to the illustrative examples shown in the accompanying drawings.